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For optimization of a sum of functions in a distributed computing environment, we present a novel communication efficient Newton-type algorithm that enjoys a variety of advantages over similar existing methods.
A generalized inverse for matrices
Roger Penrose · 1955
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Solution of sparse indefinite systems of linear equations
Christopher C. Paige and Michael A. Saunders · 1975
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LSQR: an algorithm for sparse linear equations and sparse least squares
Christopher C. Paige and Michael A. Saunders · 1982
Earlier work this paper cites.
What is invexity?
A. Ben-Israel and B. Mond · 1986
Earlier work this paper cites.
The Elements of Statistical Learning
Jerome Friedman, Trevor Hastie, and Robert Tibshirani · 2001
Earlier work this paper cites.
Numerical Optimization
Jorge Nocedal and Stephen Wright · 2006
Earlier work this paper cites.
MapReduce: simplified data processing on large clusters
Jeffrey Dean and Sanjay Ghemawat · 2008
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Invexity and Optimization
Shashi K. Mishra and Giorgio Giorgi · 2008
Earlier work this paper cites.
Spark: cluster computing with working sets
Matei Zaharia, Mosharaf Chowdhury, Michael J. Franklin, Scott Shenker, and Ion Stoica · 2010
Earlier work this paper cites.
Distributed optimization and statistical learning via the alternating direction method of multipliers
Stephen Boyd, Neal Parikh, Eric Chu, Borja Peleato, Jonathan Eckstein, et al · 2011
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MINRES-QLP: a Krylov subspace method for indefinite or singular symmetric systems
Sou-Cheng T. Choi, Christopher C. Paige, and Michael A. Saunders · 2011
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LSMR: an iterative algorithm for sparse least-squares problems
David Chin-Lung Fong and Michael Saunders · 2011
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Foundations of Machine Learning
Mehryar Mohri, Afshin Rostamizadeh, Ameet Talwalkar, and Francis Bach · 2012
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Scaling up Machine Learning: Parallel and Distributed Approaches
Ron Bekkerman, Mikhail Bilenko, and John Langford · 2012
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Understanding Machine Learning: From Theory to Algorithms
Shai Shalev-Shwartz and Shai Ben-David · 2014
DiSCO: distributed optimization for self-concordant empirical loss
Yuchen Zhang and Xiao Lin · 2015
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Revisiting distributed synchronous SGD
Jianmin Chen, Rajat Monga, Samy Bengio, and Rafal Jozefowicz · 2016
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AIDE: fast and communication efficient distributed optimization
Sashank J. Reddi, Jakub Konečnỳ, Peter Richtárik, Barnabás Póczós, and Alex Smola · 2016
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Optimization Methods for Inverse Problems
Nan Ye, Farbod Roosta-Khorasani, and Tiangang Cui · 2017
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First-Order Methods in Optimization
Amir Beck · 2017
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Cited alongside, same era.
Stochastic algorithms for inverse problems involving PDEs and many measurements
Farbod Roosta-Khorasani, Kees van den Doel, and Uri Ascher · 2014
Cited alongside, same era.
Data completion and stochastic algorithms for PDE inversion problems with many measurements
Farbod Roosta-Khorasani, Kees van den Doel, and Uri Ascher · 2014
Cited alongside, same era.
Communication-efficient distributed optimization using an approximate Newton-type method
Ohad Shamir, Nati Srebro, and Tong Zhang · 2014
Cited alongside, same era.
Alex Gittens, Kai Rothauge, Shusen Wang, Michael W. Mahoney, Jey Kottalam, Lisa Gerhardt, Michael Ringenburg, Kristyn Maschhoff, et al · 2018
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GIANT: globally improved approximate Newton method for distributed optimization
Shusen Wang, Farbod Roosta-Khorasani, Peng Xu, and Michael W. Mahoney · 2018
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Distributed second-order convex optimization
Chih-Hao Fang, Sudhir B. Kylasa, Farbod Roosta-Khorasani, Michael W. Mahoney, and Ananth Grama · 2018
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Newton-MR: Newton’s method without smoothness or convexity
Fred Roosta, Yang Liu, Peng Xu, and Michael W. Mahoney · 2018
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